Search results for: heart sound classification

Authors: Mohammed Abdullah Alshahrani

Abstract:

The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

Procedia PDF Downloads 44

Authors: Maria Luisa Barcena De Arellano, Sofya Pozdniakova, Pavelas Karkacas, Anja Kuhl, Istvan Baczko, Yury Ladilov, Vera Regitz-Zagrosek

Abstract:

Introduction: Aging is associated with deterioration of the physiological function, leading to systemic inflammation and mitochondrial dysfunction that promote the development of cardiovascular diseases. Sex differences in aging-related cardiovascular diseases have been postulated. However, their precise mechanisms remain unclear. In the current study, we aimed to investigate the sex difference in the age-related alteration in Sirt1-AMPK signaling and its relation to the mitochondrial biogenesis and inflammation. Methods: Male and female human non-disease lateral left ventricular wall tissue (young (17–40 years; n= 7 male and 7 female) and old (50–68 years; n= 9 male and 8 female)) were used. qRT-PCR, western blot and immunohistochemistry assays were performed for expression analyses of Sirt1, AMPK, pAMPK, ac-Ku70, TFAM, PGC-1α, Sirt3, SOD2 and catalase. CD68 was used as a marker for macrophages and the ratio of IL-12:IL10 (pro-inflammatory phenotype (high IL-12/low IL-10) and anti-inflammatory phenotype (low IL-12/high IL-10) was used to examine the inflammatory stage in the heart. Results: Sirt1 expression was significantly higher in young females compared to young males, whereas in aged hearts Sirt1 expression was significantly downregulated in females, but not in males. In line with the Sirt1 downregulation in aged females, acetylation of nuclear Ku70, a direct target of Sirt1, in aged female hearts was significantly elevated. The activity of AMPK was significantly decreased in aged individuals, however no sex differences in the AMPK expression or activity were found in young or old individuals. The expression of mitochondrial proteins TOM40, SOD2 and Sirt3 was significantly higher in young females compared to young males, while in aged female hearts SOD2 and TOM40 were downregulated. In addition, the expression of catalase, a key cytosolic and mitochondrial anti-oxidative enzyme was significantly higher in young females and this female sex benefit was lost in aged hearts. In addition, the number of cardiac macrophages was significantly increased in old female, but not in male hearts. Consistently, the pro-inflammatory shift in old females was further confirmed by differences in the IL12/IL10 ratio in young female cardiac tissue in a favour of the anti-inflammatory mediator IL-10 (ratio 1:4) compared to young males (ratio 1:1). The anti-inflammatory environment in the heart was lost in aged females (ratio 1:1). Conclusion: Aging leads to the significant downregulation of Sirt1 expression and elevated acetylation of Ku70 in female, but not in male hearts. Furthermore, a beneficial upregulation of mitochondrial and anti-oxidative proteins in young females is lost with aging. Moreover, the malfunctions in the expression of Sirt1 and mitochondrial proteins in aged female hearts is accompanied by a significant pro-inflammatory shift. The study provides a molecular basis for the increased incidence of cardiovascular diseases in old women.

Keywords: inflammation, mitochondrial dysfunction, aging, Sirt1-AMPK axis

Procedia PDF Downloads 258

Authors: Nan Deng, Zhenqiu Liu

Abstract:

Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

Procedia PDF Downloads 296

Authors: Zhaoqi He

Abstract:

Research Context: Endurance performance in hot environments is influenced by the interplay of hydration status and physiological responses. This study aims to investigate how dehydration, up to 2.11% body weight loss, affects the 3 km running performance of trained male athletes under conditions mimicking high temperatures. Methodology: In a randomized crossover design, five male athletes participated in two trials – euhydrated (EU) and dehydrated (HYPO). Both trials included a 70-minute preload run at 55-60% VO2max in 32°C and 50% humidity, followed by a 3-kilometer time trial. Fluid intake was restricted in HYPO to induce a 2.11% body weight loss. Physiological metrics, including heart rate, core temperature, and oxygen uptake, were measured, along with perceptual metrics like perceived exertion and thirst sensation. Findings: The 3-kilometer run completion times showed no significant differences between EU and HYPO trials (p=0.944). Physiological indicators, including heart rate, core temperature, and oxygen uptake, did not significantly vary (p>0.05). Thirst sensation was markedly higher in HYPO (p=0.013), confirming successful induction of dehydration. Other perceptual metrics and gastrointestinal comfort remained consistent. Conclusion: Contrary to the hypothesis, the study reveals that dehydration, inducing up to 2.11% body weight loss, does not significantly impair 3 km running performance in trained male athletes under hot conditions. Thirst sensation was notably higher in the dehydrated state, emphasizing the importance of considering perceptual factors in hydration strategies. The findings suggest that trained runners can maintain performance despite moderate dehydration, highlighting the need for nuanced hydration guidelines in hot-weather running.

Keywords: hypohydration, euhydration, hot environment, 3km running time trial, endurance performance, trained athletes, perceptual metrics, dehydration impact, physiological responses, hydration strategies

Procedia PDF Downloads 57

Authors: Pooja Khanal, Huaming Zhang

Abstract:

Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

Procedia PDF Downloads 191

Authors: Hosein Almasikia

Abstract:

Sarableh City is located in the west of Iran and in the seismic zone of Zagros. After the Azgole-Sarpol Zahab earthquake with a magnitude of 3.7 Richter on November 21, 2016, in some parts of Sarableh city, horrible sounds were heard by people. There is also a sound similar to the wear of the mill by some of the residents. Vibration studies and field investigations showed that these sounds have a geological origin and are emitted from the ground to the surface and may be related to geological hazards such as landslides, collapse of karstic zones, etc. In this study, an attempt has been made to investigate the possible relationship between these abnormal sounds and geological hazards.

Keywords: Sarable, Zagros, landslide, karstic zone

Procedia PDF Downloads 56

Authors: Khaled A. Alsaif, Mosaad A. Foda

Abstract:

The present work aims at development of traffic noise maps for Riyadh City using the software Lima. Road traffic data were estimated or measured as accurate as possible in order to obtain consistent noise maps. The predicted noise levels at some selected sites are validated by actual field measurements, which are obtained by a system that consists of a sound level meter, a GPS receiver and a database to manage the measured data. The maps show that noise levels remain over 50 dBA and can exceed 70 dBA at the nearside of major roads and highways.

Keywords: noise pollution, road traffic noise, LimA predictor, GPS

Procedia PDF Downloads 376

Authors: Yori Gidron, Laura Caton, Irit Ben-Aharon

Abstract:

Background: Many patients and even certain clinicians attribute cancer development to psychosocial factors. Yet, empirical data supports more the prognostic role, rather than the etiological role, of psychosocial factors in cancer. Part of the inconsistency may result from not considering possible moderating factors in the etiological role of psychosocial factors. One important candidate moderating factor is the vagal nerve, whose activity is indexed by heart-rate variability (HRV). The vagal nerve may prevent cancer since it reduces inflammation on the one hand, and since it increases anti-tumor immunity on the other hand. This study examined the moderating role of the vagus in the relation between life threatening events (LTE) and cancer development. Method: We re-analyzed data from the Lifelines Dutch longitudinal cohort study of over 150,000 people. The present study included 82,751 adults, who initially were cancer-free. We extracted information on background factors (e.g., age, gender, fat consumption), whether they ever experienced LTE, HRV and cancer diagnosis as reported by patients in annual clinic visits. HRV was derived from brief ECGs. Results: Of the full sample, 1011 people developed cancer during a follow-up. In the full sample, LTE significantly predicted cancer development (R.R = 1.063 p < .01) and HRV significantly predicted a reduced risk of cancer development (R.R = .506 p <.001). Importantly, LTE significantly predicted cancer only when HRV was low (R.R = 1.056, 95% CI: 1.007 - 1.108, p < .05) but not when HRV was high (R.R = 1.014; 95% CI: 0.916 - 1.122, p > 0.05), independent of confounders. Conclusions: To the best of our knowledge, this is the first study showing in a large sample that LTE predict cancer development, and that this occurs only when vagal nerve activity (HRV) is relatively low. These results could result from lack of vagal modulation of inflammation and also from lack of vagal modulation of stress responses. Results are in line with the cancer-protective role of the vagus. HRV needs to be routinely monitored in the population and future intervention trials need to examine whether vagal nerve activation can prevent cancer in people with LTE and with other cancer risk factors.

Keywords: cancer development, life-events, moderation, vagal nerve

Procedia PDF Downloads 168

Authors: Lauren Dhugga, Meena Parameswaran, David Blundell, Abbas Khushnood

Abstract:

Context: A multidisciplinary weekly safety briefing was implemented at the Paediatric Cardiothoracic Unit at the Freeman Hospital in Newcastle-upon-Tyne. It is a tertiary referral centre with a quarternary cardiac paediatric intensive care unit and provides complexed care including heart and lung transplants, mechanical support and advanced heart failure assessment. Aim: The aim of this briefing is to provide a structured platform of communication, in an effort to improve efficiency, safety, and patient care. Problem: The paediatric cardiothoracic unit is made up of a vast multidisciplinary team including doctors, intensivists, anaesthetists, surgeons, specialist nurses, echocardiogram technicians, physiotherapists, psychologists, dentists, and dietitians. It provides care for children with congenital and acquired cardiac disease and is one of only two units in the UK to offer paediatric heart transplant. The complexity of cases means that there can be many teams involved in providing care to each patient, and frequent movement of children between ward, high dependency, and intensive care areas. Currently, there is no structured forum for communicating important information across the department, for example, staffing shortages, prescribing errors and significant events. Strategy: An initial survey questioning the need for better communication found 90% of respondents agreed that they could think of an incident that had occurred due to ineffective communication, and 85% felt that incident could have been avoided had there been a better form of communication. Lastly, 80% of respondents felt that a weekly 60 second safety briefing would be beneficial to improve communication within our multidisciplinary team. Based on those promising results, a weekly 60 second safety briefing was implemented to be conducted on a Monday morning. The safety briefing covered four key areas (SAFE): staffing, awareness, fix and events. This was to highlight any staffing gaps, any incident reports to be learned from, any issues that required fixing and any events including teachings for the week ahead. The teams were encouraged to email suggestions or issues to be raised for the week or to approach in person with information to add. The safety briefing was implemented using change theory. Effect: The safety briefing has been trialled over 6 weeks and has received a good buy in from staff across specialties. The aim is to embed this safety briefing into a weekly meeting using the PDSA cycle. There will be a second survey in one month to assess the efficacy of the safety briefing and to continue to improve the delivery of information. The project will be presented at the next clinical governance briefing to attract wider feedback and input from across the trust. Lessons: The briefing displays promise as a tool to improve vigilance and communication in a busy multi-disciplinary unit. We have learned about how to implement quality improvement and about the culture of our hospital - how hierarchy influences change. We demonstrate how to implement change through a grassroots process, using a junior led briefing to improve the efficiency, safety, and communication in the workplace.

Keywords: briefing, communication, safety, team

Procedia PDF Downloads 138

Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

Abstract:

Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

Procedia PDF Downloads 324

Authors: Jagmeet S. Kanwal, Julia F. Langley

Abstract:

Music can heal the body, but a mechanistic understanding of this phenomenon is lacking. This study explores the effects of music presentation on neurologic and physiologic responses leading to metabolic changes in the human body. The mind and body co-exist in a corporeal entity and within this framework, sickness ensues when the mind-body balance goes awry. It is further hypothesized that music has the capacity to directly reset this balance. Two lines of inquiry taken together can provide a mechanistic understanding of this phenomenon 1) Empirical evidence for a sound-sensitive pressure sensor system in the body, and 2) The notion of a “healing center” within the brain that is activated by specific patterns of sounds. From an acoustics perspective, music is spatially distributed as pressure waves ranging from a few cm to several meters in wavelength. These waves interact and propagate in three-dimensions in unique ways, depending on the wavelength. Furthermore, music creates dynamically changing wave-fronts. Frequencies between 200 Hz and 1 kHz generate wavelengths that range from 5'6" to 1 foot. These dimensions are in the range of the body size of most people making it plausible that these pressure waves can geometrically interact with the body surface and create distinct patterns of pressure stimulation across the skin surface. For humans, short wavelength, high frequency (> 200 Hz) sounds are best received via cochlear receptors. For low frequency (< 200 Hz), long wavelength sound vibrations, however, the whole body may act as an ideal receiver. A vast array of highly sensitive pressure receptors (Pacinian corpuscles) is present just beneath the skin surface, as well as in the tendons, bones, several organs in the abdomen, and the sexual organs. Per the available empirical evidence, these receptors contribute to music perception by allowing the whole body to function as a sound receiver, and knowledge of how they function is essential to fully understanding the therapeutic effect of music. Neuroscientific studies have established that music stimulates the limbic system that can trigger states of anxiety, arousal, fear, and other emotions. These emotional states of brain activity play a crucial role in filtering top-down feedback from thoughts and bottom-up sensory inputs to the autonomic system, which automatically regulates bodily functions. Music likely exerts its pleasurable and healing effects by enhancing functional and effective connectivity and feedback mechanisms between brain regions that mediate reward, autonomic, and cognitive processing. Stimulation of pressure receptors under the skin by low-frequency music-induced sensations can activate multiple centers in the brain, including the amygdala, the cingulate cortex, and nucleus accumbens. Melodies in music in the low (< 600 Hz) frequency range may augment auditory inputs after convergence of the pressure-sensitive inputs from the vagus nerve onto emotive processing regions within the limbic system. The integration of music-generated auditory and somato-visceral inputs may lead to a synergistic input to the brain that promotes healing. Thus, music can literally heal humans through “touch” as it energizes the brain’s autonomic system for restoring homeostasis.

Keywords: acoustics, brain, music healing, pressure receptors

Procedia PDF Downloads 163

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

Procedia PDF Downloads 129

Authors: E. K. Mendez, N. A. Salazar, C. E. Orrego

Abstract:

There is undoubted proof that increasing the intake of fruit lessens the risk of hypertension, coronary heart disease, stroke, and probable evidence that lowers the risk of cancer. Proper fruit drying is an excellent alternative to make their shelf-life longer, commercialization easier, and ready-to-eat healthy products or ingredients. The conventional way of drying is by hot air forced convection. However, this process step often requires a very long residence time; furthermore, it is highly energy consuming and detrimental to the product quality. Nowadays, power ultrasound (US) technic has been considered as an emerging and promising technology for industrial food processing. Most of published works dealing with drying food assisted by US have studied the effect of ultrasonic pre-treatment prior to air-drying on food and the airborne US conditions during dehydration. In this work a new approach was tested taking in to account drying time and two quality parameters of mango slices dehydrated by convection assisted by 20 KHz power US applied directly using a holed plate as product support and sound transmitting surface. During the drying of mango (Mangifera indica L.) slices (ca. 6.5 g, 0.006 m height and 0.040 m diameter), their weight was recorded every hour until final moisture content (10.0±1.0 % wet basis) was reached. After previous tests, optimization of three drying parameters - frequencies (2, 5 and 8 minutes each half-hour), air temperature (50-55-60⁰C) and power (45-70-95W)- was attempted by using a Box–Behnken design under the response surface methodology for the optimal drying time, color parameters and rehydration rate of dried samples. Assays involved 17 experiments, including a quintuplicate of the central point. Dried samples with and without US application were packed in individual high barrier plastic bags under vacuum, and then stored in the dark at 8⁰C until their analysis. All drying assays and sample analysis were performed in triplicate. US drying experimental data were fitted with nine models, among which the Verna model resulted in the best fit with R2 > 0.9999 and reduced χ2 ≤ 0.000001. Significant reductions in drying time were observed for the assays that used lower frequency and high US power. At 55⁰C, 95 watts and 2 min/30 min of sonication, 10% moisture content was reached in 211 min, as compared with 320 min for the same test without the use of US (blank). Rehydration rates (RR), defined as the ratio of rehydrated sample weight to that of dry sample and measured, was also larger than those of blanks and, in general, the higher the US power, the greater the RR. The direct contact and intermittent US treatment of mango slices used in this work improve drying rates and dried fruit rehydration ability. This technique can thus be used to reduce energy processing costs and the greenhouse gas emissions of fruit dehydration.

Keywords: ultrasonic assisted drying, fruit drying, mango slices, contact ultrasonic drying

Procedia PDF Downloads 340

Authors: Tomás Speziale

Abstract:

This paper aims to analyse how Ian Hacking states the theoretical basis of his research on the classification of people. Although all his early philosophical education had been based in Foucault, it is also true that Erving Goffman’s perspective provided him with epistemological and methodological tools for understanding face-to-face relationships. Hence, all his works must be thought of as social science texts that combine the research on how the individuals are constituted ‘top-down’ (as in Foucault), with the inquiry into how people renegotiate ‘bottom-up’ the classifications about them. Thus, Hacking´s proposal constitutes a middle ground between the French Philosopher and the American Sociologist. Placing himself between both authors allows Hacking to build a frame that is expected to adjust to Social Sciences’ main particularity: the fact that they study interactive kinds. These are kinds of people, which imply that those who are classified can change in certain ways that prompt the need for changing previous classifications themselves. It is all about the interaction between the labelling of people and the people who are classified. Consequently, understanding the way in which Hacking uses Foucault’s and Goffman’s theories is essential to fully comprehend the social dynamic between individuals and concepts, what Bert Hansen had called dialectical realism. His theoretical proposal, therefore, is not only valuable because it combines diverse perspectives, but also because it constitutes an utterly original and relevant framework for Sociological theory and particularly for Criminology.

Keywords: classification of people, Foucault's archaeology, Goffman's interpersonal sociology, interactive kinds

Procedia PDF Downloads 337

Authors: Tarek Soliman Mostafa Soliman Al-Nana'i

Abstract:

There are non-steady voiced augments in the Semitic languages, and in the morphological and structural augmentation, two sounds were augments in all Semitic languages at the level of the spoken language and two letters at the level of the written language, which are the hamza and the ta’. This research studies only the second of them; Therefore, we defined it as “The Voiceless Dental- alveolar common augment” (VDACA) to distinguish it from the glottal sound “Hamza”, first, middle, or last, in a noun or in a verb, in Arabic and its equivalent in the Semitic languages. What is meant by “VDACA” is the ta’ that is in addition to the root of the word at the morphological level: the word “voiceless” takes out the voiced sounds that we studied before, and the “dental- alveolar common augment” takes out the laryngeal sound of them, which is the “Hamza”: and the word “common” brings out the uncommon voiceless sounds, which are sīn, shīn, and hā’. The study is limited to the ta' alone among the Arabic sounds, and this title faced a problem in identifying it with the ta'. Because the designation of the ta is not the same in most Semitic languages. Hebrew, for example, has “tav” and is pronounced with the voiced fa (v), which is not in Arabic. It is called different names in other Semitic languages, such as “taw” or “tAu” in old Syriac. And so on. This goes hand in hand with the insistence on distance from the written level and the reference to the phonetic aspect in this study that is closely and closely linked to the morphological level. Therefore, the study is “morphophonemic”. What is meant by Semitic languages in this study are the following: Akkadian, Ugaritic, Hebrew, Syriac, Mandaean, Ge'ez, and Amharic. The problem of the study is the agreement or difference between these languages in the position of that augment, first, middle, or last. And in determining the distinguishing characteristics of each language from the other. As for the study methodology, it is determined by the comparative approach in Semitic languages, which is based on the descriptive approach for each language. The study is divided into an introduction, four sections, and a conclusion: Introduction: It included the subject of the study, its importance, motives, problem, methodology, and division. The first section: VDACA as a non-common phoneme. The second: VDACA as a common phoneme. The third: VDACA as a functional morpheme. The fourth section: Commentary and conclusion with the most important results. The positions of VDACA in Arabic and other Semitic languages, and in nouns and verbs, were limited to first, middle, and last. The research identified the individual addition, which is common with other augments, and the research proved that this augmentation is constant in all Semitic languages, but there are characteristics that distinguish each language from the other.

Keywords: voiceless -, dental- alveolar, augment, Arabic - semitic languages

Procedia PDF Downloads 65

Authors: Fatma Ahmed, Heba Mostafa, Bassem Ramdan, Azza El-Soussi

Abstract:

Background: World Health Organization stated that by 2020 cardiac disease will be the number one cause of death worldwide and estimates that 25 million people per year will suffer from heart disease. Cardiac surgery is considered an effective treatment for severe forms of cardiovascular diseases that cannot be treated by medical treatment or cardiac interventions. In spite of the benefits of cardiac surgery, it is considered a major stressful experience for patients who are candidate for surgery. Prehabilitation can decrease incidences of postoperative complications as it prepares patients for surgical stress through enhancing their defenses to meet the demands of surgery. When patients anticipate the postoperative sequence of events, they will prepare themselves to act certain behaviors, identify their roles and actively participate in their own recovery, therefore, anxiety levels are decreased and functional capacity is enhanced. Prehabilitation programs can comprise interventions that include physical exercise, psychological prehabilitation, nutritional optimization and risk factor modification. Physical exercises are associated with improvements in the functioning of the various physiological systems, reflected in increased functional capacity, improved cardiac and respiratory functions and make patients fit for surgical intervention. Prehabilitation programs should also prepare patients psychologically in order to cope with stress, anxiety and depression associated with postoperative pain, fatigue, limited ability to perform the usual activities of daily living through acting in a healthy manner. Notwithstanding the benefits of psychological preparations, there are limited studies which investigated the effect of psychological prehabilitation to confirm its effect on psychological, quality of life and physiological outcomes of patients who had undergone cardiac surgery. Aim of the study: The study aims to determine the effect of prehabilitation interventions on outcomes of patients undergoing cardiac surgeries. Methods: Quasi experimental study design was used to conduct this study. Sixty eligible and consenting patients were recruited and divided into two groups: control and intervention group (30 participants in each). One tool namely emotional, physiological, clinical, cognitive and functional capacity outcomes of prehabilitation intervention assessment tool was utilized to collect the data of this study. Results: Data analysis showed significant improvement in patients' emotional state, physiological and clinical outcomes (P < 0.000) with the use of prehabilitation interventions. Conclusions: Cardiac prehabilitation in the form of providing information about surgery, circulation exercise, deep breathing exercise, incentive spirometer training and nutritional education implemented daily by patients scheduled for elective open heart surgery one week before surgery have been shown to improve patients' emotional state, physiological and clinical outcomes.

Keywords: emotional recovery, clinical recovery, coronary artery bypass grafting patients, prehabilitation

Procedia PDF Downloads 198

Authors: Patricia Portugal Marques de Carvalho Lourenço

Abstract:

Pop Music embodies both the music that is popular with the audiences and the one that is widespread amongst the general public associated with a state of mind and rhythm. Tai Chi epitomises Yin and Yang, two interconnected opposite states of being. Undivided, they are one, a neutral state of consciousness that does not swing to either pole. It remains constant and even minded. Sound flows and vibrations cause movement, a physical response to the tempo. When an excessive movement is reached leads to stillness therefore, extreme Yang leads to Yin. Pop Music and Tai Chi are comparable to state of inner being versus a state of outer being, emotional control versus emotional expression, stillness, and movement; opposites that are independent of one another yet interdependent concepts in motion.

Keywords: Pop music, C-Pop, Tai Chi, Ba Gua, communication, entertainment education

Procedia PDF Downloads 227

Authors: Martin Kendra, Tomas Skrucany, Jaroslav Masek

Abstract:

The noise is one of the negative elements influencing the human health. This article is due to the measurement of noise emitted by road vehicle and its parts during the operation. Measurement was done in the interior of common passenger cars with a digital sound meter. The results compare the noise value in different cars with different body shape, which influences the driver’s health. Transport has considerable ecological effects, many of them detrimental to environmental sustainability. Roads and traffic exert a variety of direct and mostly detrimental effects on nature.

Keywords: driver, noise measurement, passenger road vehicle, road transport

Procedia PDF Downloads 443

Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

Abstract:

Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: photovoltaic, urban residences, technology forecasting, prospecting

Procedia PDF Downloads 293

Authors: Haifeng Wang, Haili Zhang

Abstract:

Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

Procedia PDF Downloads 252

Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

Abstract:

Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

Procedia PDF Downloads 116

Authors: Neda Orak, Mostafa Zarei

Abstract:

Environmental assessment is an important session in environment management. Since various methods and techniques have been produces and implemented. Remote sensing (RS) is widely used in many scientific and research fields such as geology, cartography, geography, agriculture, forestry, land use planning, environment, etc. It can show earth surface objects cyclical changes. Also, it can show earth phenomena limits on basis of electromagnetic reflectance changes and deviations records. The research has been done on mangrove forests assessment by RS techniques. Mangrove forests quantitative analysis in Basatin and Bidkhoon estuaries was the aim of this research. It has been done by Landsat satellite images from 1975- 2013 and match to ground control points. This part of mangroves are the last distribution in northern hemisphere. It can provide a good background to improve better management on this important ecosystem. Landsat has provided valuable images to earth changes detection to researchers. This research has used MSS, TM, +ETM, OLI sensors from 1975, 1990, 2000, 2003-2013. Changes had been studied after essential corrections such as fix errors, bands combination, georeferencing on 2012 images as basic image, by maximum likelihood and IPVI Index. It was done by supervised classification. 2004 google earth image and ground points by GPS (2010-2012) was used to compare satellite images obtained changes. Results showed mangrove area in bidkhoon was 1119072 m2 by GPS and 1231200 m2 by maximum likelihood supervised classification and 1317600 m2 by IPVI in 2012. Basatin areas is respectively: 466644 m2, 88200 m2, 63000 m2. Final results show forests have been declined naturally. It is due to human activities in Basatin. The defect was offset by planting in many years. Although the trend has been declining in recent years again. So, it mentioned satellite images have high ability to estimation all environmental processes. This research showed high correlation between images and indexes such as IPVI and NDVI with ground control points.

Keywords: IPVI index, Landsat sensor, maximum likelihood supervised classification, Nayband National Park

Procedia PDF Downloads 286

Authors: Benjamin Beltzung, Marie Pelé, Julien P. Renoult, Cédric Sueur

Abstract:

To this day, it is not known if drawing is specifically human behavior or if this behavior finds its origins in ancestor species. An interesting window to enlighten this question is to analyze the drawing behavior in genetically close to human species, such as non-human primate species. A good candidate for this approach is the orangutan, who shares 97% of our genes and exhibits multiple human-like behaviors. Focusing on figurative aspects may not be suitable for orangutans’ drawings, which may appear as scribbles but may have meaning. A manual feature selection would lead to an anthropocentric bias, as the features selected by humans may not match with those relevant for orangutans. In the present study, we used deep learning to analyze the drawings of a female orangutan named Molly († in 2011), who has produced 1,299 drawings in her last five years as part of a behavioral enrichment program at the Tama Zoo in Japan. We investigate multiple ways to decipher Molly’s drawings. First, we demonstrate the existence of differences between seasons by training a deep learning model to classify Molly’s drawings according to the seasons. Then, to understand and interpret these seasonal differences, we analyze how the information spreads within the network, from shallow to deep layers, where early layers encode simple local features and deep layers encode more complex and global information. More precisely, we investigate the impact of feature complexity on classification accuracy through features extraction fed to a Support Vector Machine. Last, we leverage style transfer to dissociate features associated with drawing style from those describing the representational content and analyze the relative importance of these two types of features in explaining seasonal variation. Content features were relevant for the classification, showing the presence of meaning in these non-figurative drawings and the ability of deep learning to decipher these differences. The style of the drawings was also relevant, as style features encoded enough information to have a classification better than random. The accuracy of style features was higher for deeper layers, demonstrating and highlighting the variation of style between seasons in Molly’s drawings. Through this study, we demonstrate how deep learning can help at finding meanings in non-figurative drawings and interpret these differences.

Keywords: cognition, deep learning, drawing behavior, interpretability

Procedia PDF Downloads 155

Authors: Marrone Silverio Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner, Djamel Fawzi Hadj Sadok

Abstract:

The creation of a dataset is time-consuming and often discourages researchers from pursuing their goals. To overcome this problem, we present and discuss two solutions adopted for the automation of this process. Both optimize valuable user time and resources and support video object segmentation with object tracking and 3D projection. In our scenario, we acquire images from a moving robotic arm and, for each approach, generate distinct annotated datasets. We evaluated the precision of the annotations by comparing these with a manually annotated dataset, as well as the efficiency in the context of detection and classification problems. For detection support, we used YOLO and obtained for the projection dataset an F1-Score, accuracy, and mAP values of 0.846, 0.924, and 0.875, respectively. Concerning the tracking dataset, we achieved an F1-Score of 0.861, an accuracy of 0.932, whereas mAP reached 0.894. In order to evaluate the quality of the annotated images used for classification problems, we employed deep learning architectures. We adopted metrics accuracy and F1-Score, for VGG, DenseNet, MobileNet, Inception, and ResNet. The VGG architecture outperformed the others for both projection and tracking datasets. It reached an accuracy and F1-score of 0.997 and 0.993, respectively. Similarly, for the tracking dataset, it achieved an accuracy of 0.991 and an F1-Score of 0.981.

Keywords: RJ45, automatic annotation, object tracking, 3D projection

Procedia PDF Downloads 162

Authors: Hyun Chang Kim, Yong Hun Jung, Kyung Woon Jeung

Abstract:

Background: From the viewpoint of cardiac pump theory, the area of the left ventricle (LV) subjected to compression increases as the LV lies closer to the sternum, possibly resulting in higher blood flow in patients with LV closer to the sternum. However, no study has evaluated LV position during cardiac arrest or its relationship with hemodynamic parameters during cardiopulmonary resuscitation (CPR). The objectives of this study were to determine whether the position of the LV relative to the anterior-posterior axis representing the direction of chest compression shifts during cardiac arrest and to examine the relationship between LV position and hemodynamic parameters during CPR. Methods: Subcostal view echocardiograms were obtained from 15 pigs with the transducer parallel to the long axis of the sternum before inducing ventricular fibrillation (VF) and during cardiac arrest. Computed tomography was performed in three pigs to objectively observe LV position during cardiac arrest. LV position parameters including the shortest distance between the anterior-posterior axis and the mid-point of the LV chamber (DAP-MidLV), the shortest distance between the anterior-posterior axis and the LV apex (DAP-Apex), and the area fraction of the LV located on the right side of the anterior-posterior axis (LVARight/LVATotal) were measured. Results: DAP-MidLV, DAP-Apex, and LVARight/LVATotal decreased progressively during untreated VF and basic life support (BLS), and then increased during advanced cardiovascular life support (ACLS). A repeated measures analysis of variance revealed significant time effects for these parameters. During BLS, the end-tidal carbon dioxide and systolic right atrial pressure were significantly correlated with the LV position parameters. During ACLS, systolic arterial pressure and systolic right atrial pressure were significantly correlated with DAP-MidLV and DAP-Apex. Conclusions: LV position changed significantly during cardiac arrest compared to the pre-arrest baseline. LV position during CPR had significant correlations with hemodynamic parameters.

Keywords: heart arrest, cardiopulmonary resuscitation, heart ventricle, hemodynamics

Procedia PDF Downloads 185

Authors: Tarcisio F. Leao, Bruno Utiyama, Jeison Fonseca, Eduardo Bock, Aron Andrade

Abstract:

This work presents a blood flow estimator based in Look-Up-Table (LUT) for control of Left Ventricular Assist Device (LVAD). This device has been used as bridge to transplantation or as destination therapy to treat patients with heart failure (HF). Destination Therapy application requires a high performance LVAD; thus, a stable control is important to keep adequate interaction between heart and device. LVAD control provides an adequate cardiac output while sustaining an appropriate flow and pressure blood perfusion, also described as physiologic control. Because thrombus formation and system reliability reduction, sensors are not desirable to measure these variables (flow and pressure blood). To achieve this, control systems have been researched to estimate blood flow. LVAD used in the study is composed by blood centrifugal pump, control, and power supply. This technique used pump and actuator (motor) parameters of LVAD, such as speed and electric current. Estimator relates electromechanical torque (motor or actuator) and hydraulic power (blood pump) via LUT. An in vitro Mock Loop was used to evaluate deviations between blood flow estimated and actual. A solution with glycerin (50%) and water was used to simulate the blood viscosity with hematocrit 45%. Tests were carried out with variation hematocrit: 25%, 45% and 58% of hematocrit, or 40%, 50% and 60% of glycerin in water solution, respectively. Test with bovine blood was carried out (42% hematocrit). Mock Loop is composed: reservoir, tubes, pressure and flow sensors, and fluid (or blood), beyond LVAD. Estimator based in LUT is patented, number BR1020160068363, in Brazil. Mean deviation is 0.23 ± 0.07 L/min for mean flow estimated. Larger mean deviation was 0.5 L/min considering hematocrit variation. This estimator achieved deviation adequate for physiologic control implementation. Future works will evaluate flow estimation performance in control system of LVAD.

Keywords: blood pump, flow estimator, left ventricular assist device, look-up-table

Procedia PDF Downloads 177

Authors: M. Eckert, D. Mendes, J P. Gonçalves, C. Moço, M. Oliveira

Abstract:

The intensive extraction of natural aggregates leads to both depletion of natural resources and unwanted environmental impacts. On the other hand, uncontrolled disposal of Construction and Demolition Wastes (C&DW) causes the lifetime reduction of landfills. It is known that the European Union produces, each year, about 850 million tons of C&DW. For all the member States of the European Union, one of the milestones to be reached by 2020, according to the Resource Efficiency Roadmap (COM (2011) 571) of the European Commission, is to recycle 70% of the C&DW. In this work, properties of different types of recycled C&DW aggregates and natural aggregates were compared. Assays were performed according to European Standards (EN 13285; EN 13242+A1; EN 12457-4; EN 12620; EN 13139) for the characterization of there: physical, mechanical and chemical properties. Not standardized tests such as water absorption over time, mass stability and post compaction sieve analysis were also carried out. The tested recycled C&DW aggregates were classified according to the requirements of the European Standards regarding there potential use in concrete, mortar, unbound layers of road pavements and embankments. The results of the physical and mechanical properties of recycled C&DW aggregates indicated, in general, lower quality properties when compared to natural aggregates, particularly, for concrete preparation and unbound layers of road pavements. The results of the chemical properties attested that the C&DW aggregates constitute no environmental risk. It was concluded that recycled aggregates produced from C&DW have the potential to be used in many applications.

Keywords: recycled aggregate, sustainability, aggregate properties, European Standard Classification

Procedia PDF Downloads 658

Authors: Kwan Hee Han

Abstract:

In today’s business environments, frequent change of customer requirements is a tough challenge to manufacturing company. To cope with these challenges, a production planning and scheduling (PP&S) function might be established to provide accountability for both customer service and operational efficiency. Nowadays, many manufacturing firms have utilized PP&S software solutions to generate a realistic production plan and schedule to adapt to external changes efficiently. However, companies which consider the introduction of PP&S software solution, still have difficulties for selecting adequate solution to meet their specific needs. Since the task of PP&S is the one of major building blocks of SCM (Supply Chain Management) architecture, which deals with short term decision making in the production process of SCM, it is needed that the functionalities of PP&S should be analysed within the whole SCM process. The aim of this paper is to analyse the PP&S functionalities and its system architecture from the SCM perspective by using the criteria of level of planning hierarchy, major 4 SCM processes and problem-solving approaches, and finally propose a classification framework of PP&S solutions to facilitate the comparison among various commercial software solutions. By using proposed framework, several major PP&S solutions are classified and positioned according to their functional characteristics in this paper. By using this framework, practitioners who consider the introduction of computerized PP&S solutions in manufacturing firms can prepare evaluation and benchmarking sheets for selecting the most suitable solution with ease and in less time.

Keywords: production planning, production scheduling, supply chain management, the advanced planning system

Procedia PDF Downloads 194

Authors: Ilma Robo, Saimir Heta, Vera Ostreni, Elsaida Agrushi, Eduart Kapaj

Abstract:

Introduction: Cyclic hormonal fluctuations are known from literature to have a clinically visible effects on gingival tissue reactions, to the diagnosed processes of gingival inflammation. Materials and methods: At a total of 47 female patients, ad-hock presented at the University Clinic, were recorded data on effect of hormonal oscillations at periodontal treatment protocol. Oral examination was performed on soft tissue of gingiva and the oral mucous membrane, always respecting the air-drying procedure and then checking with free eye differences in oral mucosal relief. After the patients were informed about the study protocol, the purpose of the study and the ongoing procedure, verbal consensus was required. Results: The study was conducted in a total of 47 patients, out of which 13 patients were under the gingivitis classification, and 24 patients under the periodontal classification. Patients included in the study are divided by age, cycle week respectively 1,2,3 and 4.The younger age of female patients is more prone to the appearance of gingivitis, which is further aggravated by the effects of sexual hormones and the effect of the controlled or non-regulated fluctuations of the latter. Conclusions: The healing process is more fuel-intensive in the absence of high hormone levels, as they are these pro-inflammatory hormones, both in or near the ho Younger women are more open to volunteering in studies that record individual and study data that may last in time.

Keywords: gingiva, hormonal oscillations, female patients, mucosa, periodontal non-surgical treatment

Procedia PDF Downloads 76

Authors: Lucia Carrion Gordon, Jaime Santiago Sanchez Reinoso

Abstract:

According to the relation of Digital Preservation and the Health field as a case of study, the architectural model help us to explain that definitions. .The principal goal of Data Preservation is to keep information for a long term. Regarding of Mediacal information, in order to perform a heart transplant, physicians need to preserve this organ in an adequate way. This approach between the two perspectives, the medical and the technological allow checking the similarities about the concepts of preservation. Digital preservation and medical advances are related in the same level as knowledge improvement.

Keywords: medical management, digital, data, heritage, preservation

Procedia PDF Downloads 413